Coupling Bond Graph and Energetic Macroscopic Representation for Electric Vehicle Simulation

Silva, Luis I.; Bouscayrol, Alain; Angelo, Cristian H. De; Lemaire‐Semail, Betty

doi:10.1016/j.mechatronics.2013.12.010

Cited by 22 publications

(9 citation statements)

References 31 publications

(33 reference statements)

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“…Simulation is a key factor in the design state because it allows us to evaluate different vehicle concepts and control configurations (Silva et al, 2014). In this paper, the model is developed based on EMR method.…”

Section: Simulation Methodsmentioning

confidence: 99%

“…This method is first introduced by Bouscayrol et al (2006) and since then has been used as a representation method to develop vehicles model for simulation like in Chen et al (2008), Cheng et al (2009), andHorrein et al (2016). Due to its intrinsic feature, this method has been applied to other complex electromechanical system such as hybrid electric vehicle system (Gauchia et al, 2011), electric vehicle (Silva et al, 2014), and railcar prototype (Serge et al, 2016). Through EMR, we can design a new system, develop a new control strategy, and perform evaluation of energy consumption.…”

Section: Simulation Methodsmentioning

confidence: 99%

“…But, these resources will not last for a long time if no efforts are made to slow down the present trend. With all effort are given in all sectors to reduce pollutant emissions and new legislation on emissions of vehicle; hybrid electric vehicle (HEV) is regarded as one of the best alternative to respond well to this expectation with realistic economical, infrastructural, and customer acceptance constraints (Silva et al, 2014;Wu et al, 2016;Li et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Fuel consumption evaluation of a hybrid electric car over aggressive cycles for thermal engine optimization

Asus

2018

Int. j. adv. appl. sci.

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This paper investigates fuel consumption of a thermal engine in a hybrid electric vehicle system over aggressive cycles in order to optimize its energy consumption. The model of the system is first developed using data obtained from experiments over two aggressive driving cycles and then used to validate the model and further used as a platform to test other control strategies. The car's actual control strategy operates on high torque region of the engine to sustain battery charge and caused high fuel consumption. Based on previous researches, there are two optimal control strategies that can be implemented for a series hybrid electric vehicle system; the dynamic programming control method and the optimal torque control method. Result analysis shows that the operations of the engine are different between the two control methods; it is concentrated on high speed region for the dynamic programming control method and at the middle of the engine map for the optimal torque control method.

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Section: Simulation Methodsmentioning

confidence: 99%

Section: Simulation Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Fuel consumption evaluation of a hybrid electric car over aggressive cycles for thermal engine optimization

Asus

2018

Int. j. adv. appl. sci.

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“…Bond graphs model physical systems through a network (McBride, 2005; Silva et al, 2014), whose vertices represent physical elements (analogous to design elements and referred to by the number of energy ports that they possess) and whose edges (known as power bonds or simply bonds) represent power flow. Each bond implicitly carries an effort variable (e.g., force or voltage) and a corresponding flow variable (e.g., velocity or current).…”

Section: Function Modeling Backgroundmentioning

confidence: 99%

Function modeling using the system state flow diagram

Yildirim

Campean

Williams

2017

AIEDAM

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This paper introduces a rigorous framework for function modeling of complex multidisciplinary systems based on the system state flow diagram (SSFD). The work addresses the need for a consistent methodology to support solution-neutral function-based system decomposition analysis, facilitating the design, modeling, and analysis of complex systems architectures. A rigorous basis for the SSFD is established by defining conventions for states and function definitions and a representation scheme, underpinned by a critical review of existing literature. A set of heuristics are introduced to support the function decomposition analysis and to facilitate the deployment of the methodology with strong practitioner guidelines. The SSFD heuristics extend the existing framework of Otto and Wood (2001) by introducing a conditional fork node heuristic, to facilitate analysis and aggregation of function models across multiple modes of operation of the system. The empirical validation of the SSFD function modeling framework is discussed in relation to its application to two case studies: a benchmark problem (glue gun) set for the engineering design community; and an industrial case study of an electric vehicle powertrain. Based on the evidence from the two case studies presented in the paper, a critical evaluation of the SSFD function modeling methodology is discussed based on the function benchmarking framework established by Summers et al. (2013), considering the representation, modeling, cognitive, and reasoning characteristics. The significance of this paper is that it establishes a rigorous reference framework for the SSFD function representation and a consistent methodology to guide the practitioner with its deployment, facilitating its impact to industrial practice.

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“…The method of Bond Graphs (BG) which is the core of this study was initiated by Paynter [20] and has been developed in a number of monographs [1,3,10,26,27,28] and publications [5,8,13,15,17,19,21,22,23,25]. Thanks to a singular approach to modeling elements of different physical nature, this method is especially suited for modeling energy systems consisting of mechanical, thermal, electrical and hydraulic elements which operate in the power system of an engine room.…”

Section: Introductionmentioning

confidence: 99%

Causality in Models of Thermal Processes in Ship Engine Rooms with the Use of Bond Graph (BG) Method

Cichy

Kneba

Kropiwnicki

2017

Polish Maritime Research

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Coupling Bond Graph and Energetic Macroscopic Representation for Electric Vehicle Simulation

Cited by 22 publications

References 31 publications

Fuel consumption evaluation of a hybrid electric car over aggressive cycles for thermal engine optimization

Fuel consumption evaluation of a hybrid electric car over aggressive cycles for thermal engine optimization

Function modeling using the system state flow diagram

Causality in Models of Thermal Processes in Ship Engine Rooms with the Use of Bond Graph (BG) Method

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